Software Engineer, Machine Learning

About Chipmind

Chipmind is an AI-native company, transforming chip development with Agentic AI that automates design and verification by solving real-world tasks, accelerating the path from code to chip.

Role Description

Join Chipmind as a full-time on-site Software Engineer, Machine Learning and become a key architect in shaping the future of AI-driven chip development. In this specialized role, you will focus deeply on the trajectory, trace, and dataset layer of our stack, serving as a core contributor to our data-centric ML infrastructure. You will be instrumental in implementing the systems that capture agent reasoning from the ground up, designing the pipelines that manage complex execution traces and high-fidelity datasets. If you are a backend-leaning engineer passionate about the intersection of ML systems and hardware design, and eager to build the foundational data layers that bridge the gap between agent logic and silicon reality, we encourage you to apply and help us accelerate the path from code to chip.

Key Responsibilities

• Implement and extend the core reasoning engines and agentic workflows that drive our AI-based chip design and EDA solution.
• Integrate and optimize orchestration of AI models and multi-agent systems, focusing on performance and reliability.
• Implement post-training algorithms and retrieval systems to ensure our agents have the specific context needed for accurate RTL generation.
• Evolve and scale our development lifecycle, maturing existing DevOps and CI/CD pipelines while elevating the user experience for our pilot customers.

Minimum Qualifications

• Familiar with large language models (LLMs) and machine learning frameworks (e.g., Pytorch and TensorFlow)
• Hands-on experience with cloud infrastructure, deployment, and robust CI/CD practices.
• A passion for solving hard problems in a fast-paced environment, with the ability to both architect systems and fix bugs.
• Flexibility to handle diverse tasks ranging from cloud engineering to fine-tuning AI agents.

Nice-to-Have

• Exposure to LLM orchestration frameworks and vector databases.
• Familiarity with hardware description languages (Verilog/SystemVerilog) or the semiconductor workflow.

What We Offer

• The opportunity to make an impact on how AI develops chips.